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Integrated open-source software for multiscale electrophysiology
The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814804/ https://www.ncbi.nlm.nih.gov/pubmed/31653867 http://dx.doi.org/10.1038/s41597-019-0242-z |
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author | Nasiotis, Konstantinos Cousineau, Martin Tadel, François Peyrache, Adrien Leahy, Richard M. Pack, Christopher C. Baillet, Sylvain |
author_facet | Nasiotis, Konstantinos Cousineau, Martin Tadel, François Peyrache, Adrien Leahy, Richard M. Pack, Christopher C. Baillet, Sylvain |
author_sort | Nasiotis, Konstantinos |
collection | PubMed |
description | The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology. |
format | Online Article Text |
id | pubmed-6814804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68148042019-10-30 Integrated open-source software for multiscale electrophysiology Nasiotis, Konstantinos Cousineau, Martin Tadel, François Peyrache, Adrien Leahy, Richard M. Pack, Christopher C. Baillet, Sylvain Sci Data Article The methods for electrophysiology in neuroscience have evolved tremendously over the recent years with a growing emphasis on dense-array signal recordings. Such increased complexity and augmented wealth in the volume of data recorded, have not been accompanied by efforts to streamline and facilitate access to processing methods, which too are susceptible to grow in sophistication. Moreover, unsuccessful attempts to reproduce peer-reviewed publications indicate a problem of transparency in science. This growing problem could be tackled by unrestricted access to methods that promote research transparency and data sharing, ensuring the reproducibility of published results. Here, we provide a free, extensive, open-source software that provides data-analysis, data-management and multi-modality integration solutions for invasive neurophysiology. Users can perform their entire analysis through a user-friendly environment without the need of programming skills, in a tractable (logged) way. This work contributes to open-science, analysis standardization, transparency and reproducibility in invasive neurophysiology. Nature Publishing Group UK 2019-10-25 /pmc/articles/PMC6814804/ /pubmed/31653867 http://dx.doi.org/10.1038/s41597-019-0242-z Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Nasiotis, Konstantinos Cousineau, Martin Tadel, François Peyrache, Adrien Leahy, Richard M. Pack, Christopher C. Baillet, Sylvain Integrated open-source software for multiscale electrophysiology |
title | Integrated open-source software for multiscale electrophysiology |
title_full | Integrated open-source software for multiscale electrophysiology |
title_fullStr | Integrated open-source software for multiscale electrophysiology |
title_full_unstemmed | Integrated open-source software for multiscale electrophysiology |
title_short | Integrated open-source software for multiscale electrophysiology |
title_sort | integrated open-source software for multiscale electrophysiology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6814804/ https://www.ncbi.nlm.nih.gov/pubmed/31653867 http://dx.doi.org/10.1038/s41597-019-0242-z |
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